The methodology proposes to combine information on similar tasks using supervised learning.
Then, we need to know the operations used to obtain the comparison masks in the different tasks.
Keep in mind; all datasets perform the same preprocessing to obtain the edges and the quantized distance transform.
Thus, to obtain the objects' edges, we take the instances' masks, and we look for a difference of instance labeling.
For this, we used D-4 connectivity (up, down, right, left) [1]}, and to better highlight the boundaries, we use the morphology operation of dilation [1]}, with a structural element of 2-size and disk-shaped.
